The dosimetric impact of including the patient table in CT dose estimates

CT Image Reconstruction using NLMfuzzyCD Regularization Method

Aims and scope: Computed Tomography (CT) is one of the most efficient clinical diagnostic tools. The main goal of CT is to reproduce an acceptable reconstructed image of an object (either anatomical or functional behaviour) with the help of a limited set of its projections at different angles.

BACKGROUND

To achieve this goal, one of the most commonly iterative reconstruction algorithm called Maximum Likelihood Expectation Maximization (MLEM) is used.

OBJECTIVE

Although the conventional Maximum Likelihood (ML) algorithm can achieve quality images in CT. However, it still suffers from the optimal smoothing as the number of iterations increase.

METHODS

For solving this problem, in this paper present a novel statistical image reconstruction algorithm for CT, which utilizes a nonlocal means fuzzy complex diffusion as a regularization term for noise reduction and edge preservation.

RESULTS

The proposed model was evaluated on four test cases phantoms.

CONCLUSION

Qualitative and quantitative analyses indicate that the proposed technique has higher efficiency for computed tomography. The proposed method yields significant improvements when compare with the state-of-the-art techniques.

Diagnosis of foreign body aspiration with ultralow-dose CT using a tin filter: a comparison study

PURPOSE

Suspected airway foreign body aspiration (FBA) is a common event in paediatric emergency units, especially in children under 3 years of age. It can be a life-threatening event if not diagnosed promptly and accurately. The purpose of this study is to compare the diagnostic performance of an ultralow-dose CT (DLP of around 1 mGycm) with that of conventional radiographic methods (fluoroscopy and chest radiography of the airways) in the diagnosis of FBA children's airways.

METHODS

Retrospective cross-sectional study. Data from 136 children were collected: 75 were examined with conventional radiographic methods and 61 with ultralow-dose CT. Effective doses were compared using independent t tests. The results of bronchoscopy, if performed, were used in creating contingency 2 × 2 tables to assess the diagnostic performance between modalities. An extra triple reading of all images was applied for this purpose.

RESULTS

The effective doses used in the ultralow-dose CT examinations were lower compared with those in conventional methods (p < 0.001). The median dose for CT was 0.04 mSv compared with 0.1 mSv for conventional methods. Sensitivity and specificity were higher for ultralow-dose CT than those for conventional methods (100% and 98% versus 33% and 96%) as were the positive and negative predicted values (90% and 100% versus 60% and 91%).

CONCLUSION

Ultralow-dose CT can be used as the imaging of choice in the diagnosis of airway FBA in emergency settings, thereby avoiding concerns about radiation doses and negative bronchoscopy outcomes.

Performance of sparse-view CT reconstruction with multi-directional gradient operators

To further reduce the noise and artifacts in the reconstructed image of sparse-view CT, we have modified the traditional total variation (TV) methods, which only calculate the gradient variations in x and y directions, and have proposed 8- and 26-directional (the multi-directional) gradient operators for TV calculation to improve the quality of reconstructed images. Different from traditional TV methods, the proposed 8- and 26-directional gradient operators additionally consider the diagonal directions in TV calculation. The proposed method preserves more information from original tomographic data in the step of gradient transform to obtain better reconstruction image qualities. Our algorithms were tested using two-dimensional Shepp–Logan phantom and three-dimensional clinical CT images. Results were evaluated using the root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and universal quality index (UQI). All the experiment results show that the sparse-view CT images reconstructed using the proposed 8- and 26-directional gradient operators are superior to those reconstructed by traditional TV methods. Qualitative and quantitative analyses indicate that the more number of directions that the gradient operator has, the better images can be reconstructed. The 8- and 26-directional gradient operators we proposed have better capability to reduce noise and artifacts than traditional TV methods, and they are applicable to be applied to and combined with existing CT reconstruction algorithms derived from CS theory to produce better image quality in sparse-view reconstruction.

Estimating a size-specific dose for helical head CT examinations using Monte Carlo simulation methods

PURPOSE

Size-specific dose estimates (SSDE) conversion factors have been determined by AAPM Report 204 to adjust CTDI_vol to account for patient size but were limited to body CT examinations. The purpose of this work was to determine conversion factors that could be used for an SSDE for helical, head CT examinations for patients of different sizes.

METHODS

Validated Monte Carlo (MC) simulation methods were used to estimate dose to the center of the scan volume from a routine, helical head examination for a group of patient models representing a range of ages and sizes. Ten GSF/ICRP voxelized phantom models and five pediatric voxelized patient models created from CT image data were used in this study. CT scans were simulated using a Siemens multidetector row CT equivalent source model. Scan parameters were taken from the AAPM Routine Head protocols for a fixed tube current (FTC), helical protocol, and scan lengths were adapted to the anatomy of each patient model. MC simulations were performed using mesh tallies to produce voxelized dose distributions for the entire scan volume of each model. Three tally regions were investigated: (1) a small 0.6 cc volume at the center of the scan volume, (2) 0.8-1.0 cm axial slab at the center of the scan volume, and (3) the entire scan volume. Mean dose to brain parenchyma for all three regions was calculated. Mean bone dose and a mass-weighted average dose, consisting of brain parenchyma and bone, were also calculated for the slab in the central plane and the entire scan volume. All dose measures were then normalized by CTDI_vol for the 16 cm phantom (CTDI_vol,16 ). Conversion factors were determined by calculating the relationship between normalized doses and water equivalent diameter (D_w ).

RESULTS

CTDI_vol,16 -normalized mean brain parenchyma dose values within the 0.6 cc volume, 0.8-1.0 cm central axial slab, and the entire scan volume, when parameterized by D_w , had an exponential relationship with a coefficient of determination (R² ) of 0.86, 0.84, and 0.88, respectively. There was no statistically significant difference between the conversion factors resulting from these three different tally regions. Exponential relationships between CTDI_vol,16 -normalized mean bone doses had R² values of 0.83 and 0.87 for the central slab and for the entire scan volume, respectively. CTDI_vol,16 -normalized mass-weighted average doses had R² values of 0.39 and 0.51 for the central slab and for the entire scan volume, respectively.

CONCLUSIONS

Conversion factors that describe the exponential relationship between CTDI_vol,16 -normalized mean brain dose and a size metric (D_w ) for helical head CT examinations have been reported for two different interpretations of the center of the scan volume. These dose descriptors have been extended to describe the dose to bone in the center of the scan volume as well as a mass-weighted average dose to brain and bone. These may be used, when combined with other efforts, to develop an SSDE dose coefficients for routine, helical head CT examinations.

Compressed sensing based CT reconstruction algorithm combined with modified Canny edge detection

Given that the computed tomography (CT) reconstruction algorithm based on compressed sensing (CS) results in blurred edges, we propose a modified Canny operator that assists the CS algorithm to accurately capture an object's edge, to preserve and further enhance the contrasts in the reconstructed image, thereby improving image quality. We modified two procedures of the traditional Canny operator, namely non-maximum suppression and edge tracking by hysteresis according to the characteristics of low-dose CT reconstruction, and proposed two major modifications: double-response edge detection and directional edge tracking. The newly modified Canny operator was combined with the CS reconstruction algorithm to become an edge-enhanced CS (EECS). Both a 2D Shepp-Logan phantom and a 3D dental phantom were used to conduct reconstruction testing. Root-mean-square error, peak signal-to-noise ratio, and universal quality index were employed to verify the reconstruction results. Qualitative and quantitative results of EECS reconstruction showed its superiority over conventional CS or CS combined with different edge detection techniques, such as Laplacian, Prewitt, Sobel operators, etc. The experiments verified that the proposed modified Canny operator is able to effectively detect the edge location of an object during low-dose reconstruction, enabling EECS to reconstruct images with better quality than those produced by other algorithms.